On the Road to Self-Sufficiency after Welfare Reform: An Assessment of the Impact of Changes in Welfare Asset Limits on Auto- Ownership Rates and Employment

In this paper, we assess the impact of the easing of vehicle exemption limits and asset restrictions after the passage of welfare reform legislation on the rates of car-ownership observed among female headed households with children. Prior to the passage of the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) in 1996, nearly all states exempted only $1,500 of vehicle equity from the minimum assets test and assets were limited to$1000 in most states. Post-welfare reform, however, nearly all states increased the vehicle exemption limit, with twenty-five states exempting the entire value of a single vehicle. In addition, the overall asset test rose in most states. In this paper, we use micro-level data from the 1993 and 1996 panels of the Survey of Income and Program Participation (SIPP) from the years 1994 to 1999 to examine 1) how changes in state-level welfare rules over this time period affected auto ownership rates among those most likely at risk of receiving welfare and 2) how the resulting change in auto ownership rates affected the probability of being employed for these individuals. To identify the effect of the redefined benefit eligibility rules on auto-ownership rates, we exploit inter-state differences and changes over time in welfare eligibility rules. Once we control for individual level demographics and state-level economic conditions, our results suggest that the probability of owning a car is greater for those who reside in states with higher overall asset limits and in states with exemptions for multiple vehicles. When we look at the sample of female heads with children relative to a control group of male and female household heads without children, we also find that assessing the value of the vehicle on an equity basis (rather than fair market basis) is associated with higher rates of car ownership. Using a two stage least squares approach (2SLS) that instruments car ownership with benefit eligibility rules, we find some evidence that asset-related rules have an effect on employment outcomes via car ownership. Thus, our results shed light on the role of the changes to eligibility rules on the transition from welfare to work.

UK Alcohol Treatment trial: client-treatment matching effects

Aim To test a priori hypotheses concerning client–treatment matching in the treatment of alcohol problems and to evaluate the more general hypothesis that client–treatment matching adds to the overall effectiveness of treatment. Design Pragmatic, multi-centre, randomized controlled trial (the UK Alcohol Treatment Trial: UKATT) with open follow-up at 3 months after entry and blind follow-up at 12 months. Setting Five treatment centres, comprising seven treatment sites, including National Health Service (NHS), social services and joint NHS/non-statutory facilities. Treatments Motivational enhancement therapy and social behaviour and network therapy. Measurements Matching hypotheses were tested by examining interactions between client attributes and treatment types at both 3 and 12 months follow-up using the outcome variables of percentage days abstinent, drinks per drinking day and scores on the Alcohol Problems Questionnaire and Leeds Dependence Questionnaire. Findings None of five matching hypotheses was confirmed at either follow-up point on any outcome variable. Conclusion The findings strongly support the conclusion reached in Project MATCH in the United States that client–treatment matching, at least of the kind examined, is unlikely to result in substantial improvements to the effectiveness of treatment for alcohol problems. Possible reasons for this failure to support the general matching hypothesis are discussed, as are the implications of UKATT findings for the provision of treatment for alcohol problems in the United Kingdom

Reduction in Cholesterol Absorption Is Enhanced by Stearate-Enriched Plant Sterol Esters in Hamsters

Consumption of plant sterol esters reduces plasma LDL cholesterol concentration by inhibiting intestinal cholesterol absorption. Commercially available plant sterol esters are prepared by esterifying free sterols to fatty acids from edible plant oils such as canola, soybean, and sunflower. To determine the influence of the fatty acid moiety on cholesterol metabolism, plant sterol esters were made with fatty acids from soybean oil (SO), beef tallow (BT), or purified stearic acid (SA) and fed to male hamsters for 4 wk. A control group fed no plant sterol esters was also included. Hamsters fed BT and SA had significantly lower cholesterol absorption and decreased concentrations of plasma non-HDL cholesterol and liver esterified cholesterol, and significantly greater fecal sterol excretion than SO and control hamsters. Cholesterol absorption was lowest in hamsters fed SA (7.5%), whereas it was 72.9% in control hamsters. Cholesterol absorption was correlated with fecal sterol excretion (r = –0.72, P \u3c 0.001), liver cholesterol concentration (r = 0.88, P \u3c 0.001), and plasma non-HDL cholesterol concentration (r = 0.85, P \u3c 0.001). A multiple regression model that included each sterol ester type vs. cholesterol absorption indicated that intake of steryl stearate was the only dietary component that contributed significantly to the model (R2 = –0.75, P \u3c 0.001). Therefore, our results demonstrate that BT and SA are more effective than SO in reducing cholesterol absorption, liver cholesterol, and plasma non-HDL cholesterol concentration, suggesting that cardioprotective benefits can be achieved by consuming stearate-enriched plant sterol esters

A modified Delphi study of screening for fetal alcohol spectrum disorders in Australia

Background: There is little reliable information on the prevalence of fetal alcohol spectrum disorders (FASD) in Australia and no coordinated national approach to facilitate case detection. The aim of this study was to identify health professionals’ perceptions about screening for FASD in Australia. Method: A modified Delphi process was used to assess perceptions of the need for, and the process of, screening for FASD in Australia. We recruited a panel of 130 Australian health professionals with experience or expertise in FASD screening or diagnosis. A systematic review of the literature was used to develop Likert statements on screening coverage, components and assessment methods which were administered using an online survey over two survey rounds. Results: Of the panel members surveyed, 95 (73%) responded to the questions on screening in the first survey round and, of these, 81 (85%) responded to the second round. Following two rounds there was consensus agreement on the need for targeted screening at birth (76%) and in childhood (84%). Participants did not reach consensus agreement on the need for universal screening at birth (55%) or in childhood (40%). Support for targeted screening was linked to perceived constraints on service provision and the need to examine the performance, costs and benefits of screening. For targeted screening of high risk groups, we found highest agreement for siblings of known cases of FASD (96%) and children of mothers attending alcohol treatment services (93%). Participants agreed that screening for FASD primarily requires assessment of prenatal alcohol exposure at birth (86%) and in childhood (88%), and that a checklist is needed to identify the components of screening and criteria for referral at birth (84%) and in childhood (90%). Conclusions: There is an agreed need for targeted but not universal screening for FASD in Australia, and sufficient consensus among health professionals to warrant development and evaluation of standardised methods for targeted screening and referral in the Australian context. Participants emphasised the need for locally-appropriate, evidence-based approaches to facilitate case detection, and the importance of ensuring that screening and referral programs are supported by adequate diagnostic and management capacity

Introducing v0.5 of the AI Safety Benchmark from MLCommons

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark

Leukocyte Telomere Length in Major Depression: Correlations with Chronicity, Inflammation and Oxidative Stress - Preliminary Findings

Depression is associated with an unusually high rate of aging-related illnesses and early mortality. One aspect of “accelerated aging” in depression may be shortened leukocyte telomeres. When telomeres critically shorten, as often occurs with repeated mitoses or in response to oxidation and inflammation, cells may die. Indeed, leukocyte telomere shortening predicts early mortality and medical illnesses in non-depressed populations. We sought to determine if leukocyte telomeres are shortened in Major Depressive Disorder (MDD), whether this is a function of lifetime depression exposure and whether this is related to putative mediators, oxidation and inflammation.Leukocyte telomere length was compared between 18 unmedicated MDD subjects and 17 controls and was correlated with lifetime depression chronicity and peripheral markers of oxidation (F2-isoprostane/Vitamin C ratio) and inflammation (IL-6). Analyses were controlled for age and sex.The depressed group, as a whole, did not differ from the controls in telomere length. However, telomere length was significantly inversely correlated with lifetime depression exposure, even after controlling for age (p<0.05). Average telomere length in the depressed subjects who were above the median of lifetime depression exposure (≥9.2 years' cumulative duration) was 281 base pairs shorter than that in controls (p<0.05), corresponding to approximately seven years of “accelerated cell aging.” Telomere length was inversely correlated with oxidative stress in the depressed subjects (p<0.01) and in the controls (p<0.05) and with inflammation in the depressed subjects (p<0.05).These preliminary data indicate that accelerated aging at the level of leukocyte telomeres is proportional to lifetime exposure to MDD. This might be related to cumulative exposure to oxidative stress and inflammation in MDD. This suggest that telomere shortening does not antedate depression and is not an intrinsic feature. Rather, telomere shortening may progress in proportion to lifetime depression exposure

Introducing v0.5 of the AI Safety Benchmark from MLCommons

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark

Quantification of natural DOM from UV absorption at two wavelengths

The precise simulation of ultraviolet absorption by 23 contrasting surface-water DOM samples was achieved with a model based on two components, one absorbing light strongly (A) and the other weakly (B). The parameterised model can be used to predict [DOC] in water samples simply from absorbance values at two wavelengths, while information on DOM quality is provided by the calculated fractionation into A and B. The model was tested by predicting [DOC] for a separate dataset obtained by combining results for 12 samples each from surface waters in the UK, Canada and the USA, and from UK groundwaters. A close correlation (R2 = 0.997) was obtained, with only slight underestimation of the true [DOC]. The proportions of components A and B varied considerably among the sites, which explains why precise prediction of [DOC] from absorbance data at a single wavelength was not possible. When the model was applied to samples collected from river locations in a heterogeneous UK catchment with areas of industry and high human population, [DOC] was underestimated in many cases, which may indicate the presence of non-absorbing pollutant DOM

Charting a District's Literacy Landscape: A Path Toward Strategic Decision-Making

In late 2015, Tracy Unified School District (TUSD) was chosen along with four other California school districts in a pilot supported by the Bill & Melinda Gates Foundation. The districts in the pilot were charged to learn about and implement the Smart School Spending framework for strategic decision-making and effective resource allocation